EFFECTS OF MICROFINANCE CREDIT ON THE PERFORMANCE OF SMALL AND MEDIUM ENTEPRISES IN UASIN GISHU COUNTY, KENYA

RESEARCH PROJECT SUBMITTED TO CUEA, GABA IN PARTIAL FULFILLMENT FOR THE AWARD OF BACHELORS DEGREE

EFFECTS OF MICRO FINANCE CREDIT ON THE PERFORMANCE OF SMALL AND MEDIUM ENTREPRISE IN UASIN GISHU COUNTY, KENYA

BY KIBET K DENNIS BCOM/GC/543/11/12

RESEARCH PROJECT SUBMITTED TO CUEA, GABA IN PARTIAL FULFILLMENT FOR THE AWARD OF BACHELORS DEGREE

DECLARATION
Declaration by the Student
I, the undersigned, declare that this project is my original work and that it has not been presented in any other university or institution for academic credit.
KIBET K DENNIS
BCOM/ GC/543/11/12

Signature.................................................... Date....................................

Declaration by the Supervisors
This research project has been submitted for examination with our approval as university supervisors.
Dr. Gedion Omwono
Catholic University of Eastern Africa, GABA Campus
Signature.................................................... Date....................................

ABSTRACT

This study discusses the effects of Microfinance credit on the performance of Small and Medium enterprises in Uasin Gishu County, Kenya. This study was guided by the following research questions, what are the effects of MFIs credit on the growth of SMEs capital? How does MFIs credit effect growth of SMEs human resource? To what extend does MFIs credit improve financial assistance towards SME growth? Why is micro finance credit not popular in the county? The study targeted over 5,000 entrepreneurs with a sample size of 100 SMEs. The study employs a survey design. The instruments used in this study were open and closed ended Questionnaires and observation and interview guide. Face and content validity was used to ascertain the conceptual clarity and investigative bias. The study was guided by pecking order theory, the study delimit itself to Uashin Gishu County with a simple random sampling of 100 SMEs. Data was presented through the use of frequency tables, pie charts and percentages. Data was analyzed using ANOVA. In the final analysis, the research clearly found that MFC have a positive effect on the performance of SMEs with a level of significant of less than 5%. In order to enhance a sustained and accelerated growth in the operations of SMEs credits should be client-oriented and not product- oriented. Proper and extensive monitoring activities should be provided for clients who are granted loans. It’s concluded that MFIs are concerned with provision of financial services to people who are economically poor and who therefore experience financial exclusion in that they do not have ready access to mainstream, commercial financial services. It is concerned with provision of financial services to poor people using means which are just, fair and sustainable for example they accept social collateral rather than financial collateral, access to larger amounts of loan if repayment is performance is positive, easy way to access finance in not much paper work, and easy and short procedures.

DEDICATION
I dedicate this study to my parents Mr. Luke Chemase and Mrs. Agnes Chemase for their sacrifice, encouragement and support. To my brothers Steve, Brian and sister Sheila also my friends for their encouragements and support

ACKNOWLEDGEMENTS
It is my pleasure to express my sincere gratitude and appreciation to my project supervisor Dr. Gedion Omwono, for his patience, positive criticism, passion to see me excel and persistent guidance in preparing this project. Thank you so much for your time, I enjoyed being your student. I am grateful to all lecturers in Finance department, The Catholic University of Eastern Africa, for their guidance and support during my studies. I greatly appreciate the companionship of my colleagues in the BCOM class 2011/2012 and 2012/2013 class cohort for the support and tolerance throughout the program. The discussions really helped and may our good Lord reward you abundantly. I would like to sincerely thank my parents for their prayers and encouragement. Further, I appreciate the support of my immediate family here in Langas. You are simply the best. My greatest gratitude is to God the Almighty. He is a faithful God and may His name be praised forever.

ACRONYMS
ELD Eldoret
UG Uasin Gishu
AMFIs Association of Microfinance Institutions
IEA Institute of Economic Affairs
SED Society for Economic Development
LSE Large Scale Enterprises
MFIs Micro Finance Institutions
MSE Micro Small Enterprise
NGOs Non-Governmental Organizations
SHGs Self Help Groups
SMEs Small and Medium Enterprises
IEA Institute of Economic Affairs
ROA Return on Asset
ROE Return on Equity
ROI Return on Investment
ROS Return on Sale
GOK Government of Kenya
KIPPRA Kenya Institute for Public Policy Research and Analysis
K-REP Kenya Rural Enterprise Program
KSHS Kenya Shillings
MFC Micro Finance Credit

OPERATIONAL DEFINITION OF TERMS

Chamas self-help groups where they save among themselves and borrow when in need
Microfinance finance of low amount of money
Installments how refunds of the originally given amount are to be distributed
Self-employment doing oneself income generating activity
Rate of asset how business assets will increase
Rate of equity the way at which business equity will increase
Rate of income how business income will be affected
Rate of sale how the business sales will be affected by the development

CHAPTER ONE 1.0 INTRODUCTION
1.1. Background to the Problem
In recent years, both developed and developing countries support for SMEs development and growth has increased. This is because of the contribution of SMEs to the employment creation. Evidence shows that a dynamic and growing SMEs sector can contribute to the achievement of a wide range of development objectives, including: the attainment of income distribution and poverty reduction (DFID, 2000); creation of employment (Daniels & Ngwira, 1993); savings mobilization (Beck et al., 2005); and production of goods and services that meet the basic needs of the poor (Cook & Nixson, 2000).Phillips & Kirchhoff (1989) cited by Pasanen (2006) found that young firms that grow have twice the probability of survival as young non-growing firms. It has been also found that strong growth may reduce the firm’s profitability temporarily, but increase it in the long run (Pasanen, 2003). The growth of SMEs is believed to be a desirable end as the key drivers of employment and economic development.
Small and Micro enterprises are the backbone of many economies in Sub-Saharan Africa (SSA) and hold the key to possible revival of economic growth and the elimination of poverty on a sustainable basis. Despite the substantial role of the SMEs in SSA’s economies, they are denied official support, particularly credit, from institutionalized financial service organizations that provide funds to businesses. According to, these enterprises account more than one – half of the economic activities of the countries within the sub- region, by contributing about 12% and 34% of rural and urban employment activities in Tanzania. Numerous evidences have pointed to the fact that the number of these enterprises in Tanzania is declining at an alarming rate and little has been achieved in Tanzania, despite of the many efforts done to fight for poverty reduction (Hamisi Madole, 2013)
Lack of access to finance has been identified as one of the major constraints to small business growth (Lawson, 2007). The reason is that provision of financial services is an important means for mobilizing resources for more productive use (Watson & Everett, 1999). Performance of SMEs depends a lot on microfinance institutions support; therefore governments have introduced policies that enable SMEs to access credit from the microfinance institutions.
The importance of financial services to SMEs cannot be overemphasized. SMEs particularly those in developing countries like Tanzania need a range of enabling and sustainable financial services in order to enable them effectively exploit abundant resources in their areas and fulfill their productive potential (Nwanna, 2000)
The introduction of MFI’s in Tanzania is seen as the best alternative source of financial services for low income earners and their SMEs as a means to raise their income, hence reducing their poverty level and contributing in country economy (Kessy & Urio, 2006). the service of microfinance institution to majority of Tanzanians who are low income earners have created opportunity to them including managing scarce household and enterprises resources more efficiently, protection against financial risks by taking advantages of investment opportunities and gaining economic returns (Chijoriga, 2000). Micro finance enables clients to protect, diversify and increase their incomes, as well as to accumulate assets, reducing their vulnerability to income and consumption shocks (Robinson, 2002).
Since Kenya attained independence in 1963, considerable efforts have been directed towards the nation’s industrial development. The initial efforts were government-led through the vehicle of large industry, but lately emphasis has shifted to Small and Medium Enterprises (SMEs). The government encourages the microfinance crediting through licensing them and also giving them credit by loaning them through the Central Bank of Kenya.
In UasinGishu county micro finance credit is not new in the sense that they used to loan each other through the popularly known chamas known in the region as merry go round. With the introduction of the microfinance institutions UG residents have exploited it hence effective business.

1.2 Statement of the Problem
Ideally, Microfinance is a source of financial services for entrepreneurs and small businesses lacking access to banking and related services. The two main mechanisms for the delivery of financial services to such clients are: (1) relationship-based banking for individual entrepreneurs and small businesses; and (2) group-based models, where several entrepreneurs come together to apply for loans and other services as a group. Sometimes, microfinance is described as the supply of financial services to low-income employees, which is closer to the retail finance model prevalent in mainstream banking. Several microfinance institutions have succeeded in reaching the poorest of the poor by devising innovative strategies. These include the provision of small loans to poor people, especially in rural areas, at full-cost interest rates, without collateral, that are repayable in frequent installments. Borrowers are organized into groups, which reduces the risk of default. These are also effective mechanisms through which to disseminate valuable information on ways to improve the health, legal rights, sanitation and other relevant concerns of the poor. Above all, many microcredit programmes have targeted one of the most vulnerable groups in society - women who live in households that own little or no assets. By providing opportunities for self-employment.
Currently most entrepreneurs have adopted the culture of getting capital from MFIs, than the commercial banks because of the ease in MFI credit. More so as top up they also continue with the tradition of saving and taking loans from groups (Chamas) within the contest of SHGs.
Dellien et al. (2005) discusses key differences between the group lending and individual lending programs. First, because time and effort is invested in building social networks that enable groups to select members who are creditworthy under group lending, the role of loan officers is to provide structure, training on loan processes and administrative support. Under individual lending, loan officers bear principle responsibility for loan decisions; they screen, and monitor their clients as well as come up with mechanisms of enforcing repayment. Second, the principle incentives for repayment of group loans is joint liability, group reputation, credit rating and future access to credit for each member, all of which are directly contingent on each member upholding their obligations. On the other hand, individual lending programs use a variety of incentives such as collateral requirements, co-signers and guarantors to promote repayment and repayment discipline is created by strict enforcement of contracts.
Each of the two lending programs has its strengths and weaknesses. Armendáriz & Morduch (2000) observe that group meetings facilitate education and training useful for clients with small experience and improve financial performance of their businesses. Other researchers (Godquin, 2004 & Madajewicz, 2011) argue that group lending helps mitigate the risks associated with information asymmetry: for instance, because group borrowers are linked by joint liability, if one of them switches from safe to risky project (moral hazard), the probability that her partner will have to pay the liability rises. This gives group members the incentive to monitor each other. The reduction in group members’ default through peer pressure and social ties has also been discussed (Guttman, 2007, Dixon et al., 2007, Al-Azzam et al., 2011). However, Maria (2009) points out that group monitoring may be rendered ineffective where social ties are loose and the cost of monitoring each other high. As cited by Odongo kodongo (2013) on the study, Individual lending versus group lending: An evaluation with Kenya's microfinance data

Several studies have been done on this area, Waithanji, S .Wakaba,( 2014 )did a research on the effect of microfinance credit on the financial performance of small and medium enterprises in kiambu county and found that all SMEs borrow investment capital and they use it for the purpose in which they borrowed for, most of them do not have other source of financing other than from micro-finance institutions and they did not have other form of financing before they started receiving financing from microfinance institutions. Another study done by Hamisi Madole, (2013) on the impact of microfinance credit on the performance of SMEs in Tanzania found that; the role of financial institutions toward SMEs success is a vital important. This study therefore, examine the effects of micro-finance credit on the performance of small and medium enterprises in Uashin Gishu County, Kenya

1.3 Research Questions
The study was guided by the following research questions: (i) What are the effects of MFIs credit on the growth of SMEs capital? (ii) How does MFIs credit effect growth of SMEs human resource? (iii) To what extend does MFIs credit improve financial assistance towards SME growth? (iv) Why is micro finance credit not popular in the county?

1.4 Significance of the Study
The study will help MFIs to better understand the effects of credit on the performance of SMEs in order to implement better and effective programs in the future.
More so will better expose possible areas of improvement in micro financing in Kenya.
It sheds light on the relationship between microfinance credits and the performance of small and medium enterprise. This can help them to come out with substantive possible alternative policy interventions which might help to address problems and challenges which small and medium enterprises face.
It can also offer empirical evidence on the impact of microfinance credit on the performance of small and medium enterprises for use in short term and long term interventions especially in the fight against poverty.
It also enlighten the government and the public on the role of MFI in the SMEs sector

1.5 Scope and Delimitation of the Study
The study delimited to Uasin Gishu county, it also delimit itself to effects of to a period of one year, and to the study of effects of micro finance credit on the performance of small and medium enterprise in Uasin Gishu County, Kenya. It delimited itself from May to August 2015.

1.6 THEORETICAL FRAMEWORK
The Pecking-order model. This model was initially proposed by Myers (1994) and suggests that firms tend to finance their needs in a hierarchical fashion, first using internally available funds, followed by debt, and finally external equity.
This model attempts to avoid the resulting risk that profitable investment projects will be foregone by seeking to finance them internally. If retained earnings are insufficient, they will opt for debt rather than equity finance, because debt providers, with a prior claim on the firm’s assets and earnings, are less exposed than equity investors to errors in valuing the firm. Managers will only opt for equity finance as a last resort in this model. In these circumstances, corporate gearing will reflect a company’s need for external funds and unlike the trade-off approach there will not necessarily be any target or optimal level of gearing.
The pecking-order model to a great extent tells the way certain characteristics of a firm may influence gearing decisions. As Myers suggested, some entities follow a certain hierarchy to determine which the next alternative source of finance is, and that fear of intrusion and dilution of power in an entity may cause a certain sources to be selected. Myers (1994) suggests that issuing debt secured by collateral may reduce the asymmetric information related costs in financing. The difference in information sets between the parties involved may lead to the moral hazard problem (hidden action) and/or adverse selection (hidden information). Hence, debt secured by collateral may mitigate asymmetric information related cost in financing. This theory has numerous advantages which include: One is able to exploit all avenues first before resorting to debt, takes to consideration profitable investments, and takes to consideration the urgency project and hierarchy of alternative source of finance. However, it also has the following limitation Leads to moral hazard problem. This study was guided by the aspect which attempts to avoid the resulting risk that profitable investment projects will be foregone by seeking to finance them internally.

1.8 Conceptual Framework Microfinance credit
Favorable grace periods
Favorable initial ceiling amounts
Achievable collaterals
Small and Medium Enterprise performance
-Rate of asset
-Rate of equity
-Rate of investment
-Rate of sale
-
Independent variables
Dependent variable
MICRO-FINCE CREDIT
The study adopted a conceptual framework that explained the effects of influence of micro-finance credit on the performance of SMEs in Uasin Gishu County.

CHAPTER TWO 2.0 LITERATURE REVIEW
2.1 Critical Review of Theories
The Pecking order model
This model attempts to avoid the resulting risk that profitable investment projects will be foregone by seeking to finance them internally. If retained earnings are insufficient, they will opt for debt rather than equity finance, because debt providers, with a prior claim on the firm’s assets and earnings, are less exposed than equity investors to errors in valuing the firm. Managers will only opt for equity finance as a last resort in this model. In these circumstances, corporate gearing will reflect a company’s need for external funds and unlike the trade-off approach there will not necessarily be any target or optimal level of gearing. This model was initially proposed by (Myers 1994) and suggests that firms tend to finance their needs in a hierarchical fashion, first using internally available funds, followed by debt, and finally external equity.
Central concern appears to be a concentration by small firms on “sources of finance that minimize intrusion into business” (Lopez-Gracia & Aybar-Arias, 2000). Consequently firms do not have an optimal debt-equity ratio but rather it varies, justified by the firm’s need of external finance. The pecking-order model to a great extent tells the way certain characteristics of a firm may influence gearing decisions. As Myers suggested, some entities follow a certain hierarchy to determine which the next alternative source of finance is, and that fear of intrusion and dilution of power in an entity may cause a certain sources to be selected. (Myers 1994) suggests that issuing debt secured by collateral may reduce the asymmetric information related costs in financing. The difference in information sets between the parties involved may lead to the moral hazard problem (hidden action) and/or adverse selection (hidden information). Hence, debt secured by collateral may mitigate asymmetric information related cost in financing. (Madole, H 2013)
The Poverty Alleviation Theory
The pressing need for rural economy is to create job for large unemployed and under employed labour force. It is customarily argued that jobs can be created either by generating wage employment or by promoting self-employment in non-farm activities. Creation of employment requires investment in small working capital. (Wahid, 1994) unfortunately income from other sources is so low that they cannot generate investible surplus on their own. Thus obtaining credit under certain circumstances can help the poor accumulate their own capital and thus improve their living standard through the income generated from investments.

The trade – off Model.
Different explanations provide the theoretical basis for the decision taken by firms in the respective areas on the justification for the choice of financing sources and the appropriate mix. The trade-off model postulates that the firm will aim at the optimal gearing levels that will balance the tax benefits of additional debt with the expected costs of financial distress as the level of indebtedness rises (Brierley, 2001; Bunn, Cunningham, & Drehmann, 2005). Considering non-tax benefits of debt such as information asymmetries between lenders and borrowers, managers may raise equity only when company’s shares seem overvalued. Investors will consequently discount any new and existing shares when a new equity issue is announced.
Cassar & Holmes, (2001) found out that firms’ trade-off several aspects, including the exposure of the firm to bankruptcy and agency costs against the tax benefits associated with debt use. Firms are faced with higher cost of capital because of the increased risk of liquidation and thus they tend to avoid debt. However, firms use debt in order to enjoy tax benefits as a trade-off with the costs associated with bankruptcy and agency, and this implies that there is an optimal debt-equity ratio for the firm, which changes as benefits and costs alter over time (Modigliani & Miller, 1963). This model provides elaborate explanation for the objectives previously outlined in 1.3 where there is a need to understand the justifications for a particular mix of sources of capital due to various benefits and risks embedded in each of these. It is clearly evident that managers will opt for the mix of sources that minimizes the cost of capital but at the same time not exposing the entity to the factors that may adversely affect the going concern of the firm.

2.2 Criticism of the theories
The Pecking order model
This model attempts to avoid the resulting risk that profitable investment projects will be foregone by seeking to finance them internally. If retained earnings are insufficient, they will opt for debt rather than equity finance, because debt providers, with a prior claim on the firm’s assets and earnings, are less exposed than equity investors to errors in valuing the firm. Managers will only opt for equity finance as a last resort in this model. In these circumstances, corporate gearing will reflect a company’s need for external funds and unlike the trade-off approach there will not necessarily be any target or optimal level of gearing. However it focuses only on the productivity as the only tool to measure the performance of the enterprises it doesn’t take to consideration other measures
The pecking-order model to a great extent tells the way certain characteristics of a firm may influence gearing decisions. As Myers suggested, some entities follow a certain hierarchy to determine which the next alternative source of finance is, and that fear of intrusion and dilution of power in an entity may cause a certain sources to be selected. Myers (1994) suggests that issuing debt secured by collateral may reduce the asymmetric information related costs in financing. The difference in information sets between the parties involved may lead to the moral hazard problem (hidden action) and/or adverse selection (hidden information). Hence, debt secured by collateral may mitigate asymmetric information related cost in financing. This theory has numerous advantages which include: One is able to exploit all avenues first before resorting to debt, takes to consideration profitable investments, and takes to consideration the urgency project and hierarchy of alternative source of finance. However, it also has the following limitation Leads to moral hazard problem. This study was guided by the aspect which attempts to avoid the resulting risk that profitable investment projects will be foregone by seeking to finance them internally.

Microfinance Credit Theory
Microfinance in Kenya is now fully fledged sector. (Dondo, 1999) traced the history of MFIs in Kenya to the mid-1950s when the joint Loan Board Scheme was established to provide credit to indigenous Kenyans with small trading business loans. The Microfinance Institutions in sector in Kenya has grown since it inceptions in the 1970s and is one of the most established in Africa (Kashangaki et al, 1999). The birth of specialized microfinance in Kenya was in the 1980s when Kenya Rural Enterprises Fund (K-REP) and the Kenya Women Finance Trust (KWFT) were established. In the 1990s more MFIs emerged for example Faulu Kenya, Small and Medium Enterprise Program commonly known as SMEP and Jamii Bora
The concept of group lending is commonly heralded as the main innovation of microfinance and claims to provide an answer to the shortcomings of imperfect credit markets, in particular to the challenge of overcoming information asymmetries. Information asymmetries may lead to the distinct phenomena of adverse selection and moral hazard. In the case of adverse selection, the lender lacks information on the riskiness of its borrowers. Riskier borrowers are more likely to default than safer borrowers, and thus should be charged higher interest rates to compensate for the increased risk of default (Rahman, 2010).
Accordingly, safer borrowers should be charged less provided each type can be accurately identified. Since the lender has incomplete information about the risk profile of its borrowers, higher average interest rates are passed on to all borrowers irrespective of their risk profile. In moral hazard generally refers to the loan utilization by the borrower that is the lender cannot be certain a loan, once disbursed, is used for its intended purpose, or that the borrower applies the expected amounts of complementary inputs, especially effort and entrepreneurial skill, that are the basis for the agreement to provide the loan. If these inputs are less than expected then the borrower may be less able to repay it (Rahman, Davanzo & Sutradhar, 2006)
The standard model of lending commonly contains two mechanisms which address the issue of information asymmetries: assortative matching or screening to deal with adverse selection, and peer monitoring to overcome moral hazard. Early models were developed by (Stiglitz, 1990), (Swain, 2008).These models examined how group liability schemes resolve moral hazard and monitoring problems. Other models developed by (Rafiq et al, 2009). (Gangopadhyay et al. 2005) were inspired by (Stiglitz & Weiss, 1981) and focused on adverse selection and screening mechanisms. Moreover, social ties among group members, i.e. social connections in

the language of (Anand & Kanbur, 1993), also referred to as social capital; appear to play an important role in the context of group liability schemes in terms of enhancing repayment behavior, as theorized by (Pisani & Yoskowitz, 2010).
Credit Access Theory
The credit theory was postulated by Stiglitz & Weiss (1981), they provided a framework for analyzing financial market inefficiencies. This framework provides that information asymmetry is the main cause of financial market malfunctioning in developing countries. Financial institutions that advance loans to economic agents are not only interested in the interest they receive on loans, but also the risks of such loans.
Most financial institutions screen and monitor borrowers more efficiently than other investors can. They are specialized in gathering private information and treating it. Managing money and deposit accounts, banks own highly strategic information on firms‟ receipts and expenditures as well as the way that firms develop (Kashyap, Stein & Wilcox, 1993).Despite this plethora of information, relationships between bankers and firms are not perfect. Banks suffer from informational asymmetries such that evolution of prices (interest rates) cannot clear the credit market. Finally, non- walrassian equilibrium arises with a fringe of unsatisfied agents (Pinaki, 1998).
In reference to (Stiglitz & Weiss, 1981) adverse selection and thus credit rationing still occurs if banks require collateral. They argue that low-risk borrowers expect a lower rate of return on average. Thus, they are less wealthy than high-risk borrowers on average after some periods. Low-risk borrowers are therefore not able to provide more collateral. Increasing collateral requirements may have the same adverse selection effect as a higher interest rate. Instead Walsh (1998) argues that banks only offer contracts in which they simultaneously adjust interest rates and collateral requirements. He proved that there is always a combination of interest rate and collateral requirements so that credit rationing does not occur (Jaffee & Russell, 1996).
The proponents of this theory argue that the most interesting form of credit rationing is equilibrium rationing, where the market has fully adjusted to the public whereby banks ration credit free, available information and where demand for loans for a certain market interest rate is greater than supply.(Stiglitz & Weiss, 1981) explains that credit rationing occurs if a financial institution charge the same interest rate to all borrowers, because they cannot distinguish between borrowers and screening borrowers perfectly is too expensive.
Both assumptions are very simplifying and do not occur in this manner in the real world. Banks are usually able to distinguish their borrowers up to a certain degree.
The Theory of Financial Intermediation
According to the theory of intermediation, current theories of the economic role of financial intermediaries build on the economics of imperfect information that began to emerge during the 1970s with the seminal contributions of Akerlof (1970) & Spence, 1973) and (Bernanke & Blinder, 1992).Financial intermediaries exist because they can reduce information and transaction costs that arise from an information asymmetry between borrowers and lenders. Financial intermediaries thus assist the efficient functioning of markets, and any factors that affect the amount of credit channeled through financial intermediaries can have significant macroeconomic effects (Spence, 1973).
There are two strands in the literature that formally explain the existence of financial intermediaries. The first strand emphasizes financial intermediaries‟ provision of liquidity. The second strand focuses on financial intermediaries‟ ability to transform the risk characteristics of assets. In both cases, financial intermediation can reduce the cost of channeling funds between borrowers and lenders, leading to a more efficient allocation of resources. (Bernanke & Gertler 1995) analyzed the provision of liquidity and the transformation of illiquid assets into liquid liabilities by banks. In (Adolfson 2002) model, depositors are risk averse and uncertain about the timing of their future consumption needs. Banks can improve on a competitive market by providing better risk sharing among agents who need to consume at different times.
An intermediary promising investors a higher payoff for early consumption and a lower payoff for late consumption relative to the non-intermediated case enhances risk sharing and welfare. The optimal insurance contract in (Claus & Smith, 1999).Financial model is a demand deposit contract, but it has an undesirable equilibrium, in which all depositors panic and withdraw immediately, including even those who would prefer to leave their deposits in the bank if they were not concerned about the bank failing (Adolfson, 2002).
The proponents of this theory explain that the modern theory of financial intermediation, financial intermediaries are active because market imperfections prevent savers and investors from trading directly with each other in an optimal way.
The most important market imperfections are the informational asymmetries between savers and investors. Financial intermediaries, banks especially, fill as agents and as delegated monitors‟ information gaps between ultimate savers and investors. They screen and monitor investors on behalf of savers to ensure the sustainability of financial intermediation, safety and soundness regulation has to be put in place (Bernanke & Blinder, 1992).

2.2 Empirical Review

Numerous studies have been done on micro finance. Quaye Daniel Nii Obli (2011) did a study on the effect of micro finance institutions on the growth of small and medium scale enterprises (SMESs); a case study of selected SMEs in the kumasi metropolis. The study examined the detailed profile of SMEs in the Kumasi Metropolis of Ghana, the contribution of MFIs to entrepreneurial growth, the challenges encountered by SMEs in accessing credit and the rate of credit utilization by SMEs. An analysis of the profile of SMEs show that most SMEs are at their Micro stages since they employ less than six people and the sector is hugely dominated by the commerce sub-sector. The research also indicates that MFIs have had a positive effect on the growth of SMEs.
A study done by Hamisi Madole on the impact of microfinance credit on the performance of SMEs in Tanzania, shows that credit obtained from NMB Bank in Morogoro, SMEs have been able to improve businesses in term of: increased business profit, increased employees, increased sales turnover, increased business diversification, increased business capital and assets as well as reduction of poverty among customers surveyed. Result also shows that collateral, age or experience of the SMEs owners, and, size of the firm influence the access of credit. The study concluded most of the small businesses depend on bank loan for business capital growth. Bank loan especially NMB loan plays a very crucial role to promote small business growth. Although some of the small businesses fail to repay bank loan due to various reasons such as grace period, moral hazard and high interest rate. In regard to the findings, however, it was recommended that MFIs should increase credit and enhances participation in SMEs financing, in order to sustain the growth and maximal contribution to economic growth and development of the nation.
Government and MFIs should enhance the out-reach of microfinance through creating awareness of the activities and operations to SMEs especially those in rural and semi-urban areas that are yet to appreciate the benefits of the scheme.

Another study was done by Koech, (2011) conducted a study to find out the financial constraints that hinder growth of SMEs in Kenya. The researcher adapted the case study approach and targeted SMEs in Kamukunji District. The study used structured questioners as main tool for data collection. Data was analyzed and by explanatory factor analysis and descriptive analysis was the help of SPSS to obtain percentages and frequency distribution tables. The factor hindering growth of SMEs were identified as capital access, cost, capital market, collateral requirements, information access, capital management and cost of registration. The study recommended that business financiers through loans consider reducing collateral requirements to facilitate SMEs easy access to loans.
( Waithanji, S . W, 2011) did a study on the effect of microfinance credit on the financial performance of small and medium enterprises in kiambu county, Kenya. The research problem was studied through the use of survey design. Out of the 2,061 SMEs licensed, the study randomly sampled 60 SME‟s. The study found that there is a direct relationship of access to credit and financial performance of the companies. The study also concludes that the enterprises benefit from loans from microfinance institutions, the SMEs seek financial assistance from the MFIs due to interest rate, easy loan repayment and amount offered. There is need to provide an enabling environment for SME‟s to grow and thrive, therefore there is a need to develop strategies to enhance increased access to microfinance credit by SME‟s from commercial banks and microfinance institutions. It is important for the government to set up policies that will ease microfinance credit to SME‟s.

2.3 critic of the review
Several studies have been done on this area, Waithanji S. W, ( 2014 )did a research on the effect of microfinance credit on the financial performance of small and medium enterprises in kiambu county and found that all SMEs borrow investment capital and they use it for the purpose in which they borrowed for, most of them do not have other source of financing other than from micro-finance institutions and they did not have other form of financing before they started receiving financing from microfinance institutions. Another study done by Hamisi Madole, (2013 ) on the impact of microfinance credit on the performance of SMEs in Tanzania found that; the role of financial institutions toward SMEs success is a vital important. Quaye Daniel Nii Obli (2011) did a study on the effect of micro finance institutions on the growth of small and medium scale enterprises (SMESs); a case study of selected SMEs in the kumasi metropolis.But none has done the study on the effect of micro finance credit on the performance of small and medium enterprises in Uasin Gishu County

2.4 KNOWLEDGE GAP
Several studies have been done on this area, Waithanji S. W, ( 2014 )did a research on the effect of microfinance credit on the financial performance of small and medium enterprises in kiambu county and found that all SMEs borrow investment capital and they use it for the purpose in which they borrowed for, most of them do not have other source of financing other than from micro-finance institutions and they did not have other form of financing before they started receiving financing from microfinance institutions. Another study done by Hamisi Madole, (2013 ) on the impact of microfinance credit on the performance of SMEs in Tanzania found that; the role of financial institutions toward SMEs success is a vital important. This study therefore, examine the effects of micro-finance credit on the performance of small and medium enterprises in Uashin Gishu County, Kenya

CHAPTER THREE 3.0 RESEARCH DESIGN AND METHODOLOGY
3.1 Research Design
The study employed a survey design. (Mugenda & Mugenda, 2003) define a survey is an attempt to collect data from members of a population in order to determine the current status of that population with respect to one or more variables.

3.2 Target Population
(Cohen, 2000) shows that population is a group from which the study expects to get useful information and draw conclusions for the study. Target population for this study was over 5,000 entrepreneurs from small and medium enterprise in Uasin Gishu County.
3.3 Description of Sample and Sampling Procedures
When conducting this study, the researcher applied probability sampling procedures on 100 SMEs.

3.4 Description of Research Instruments
This study adopted open and closed ended questionnaires, interview guide and observation

3.4.1 Questionnaires
Open and closed ended Questionnaire we reused to collect data as they were distributed to all the 100 sampled entrepreneurs in Uasin Gishu County to fill them so as to collect raw data
3.4.2 Interview guide
Interviews schedules were used to collect data from the informant while seeking in-depth information from the managers of the micro-finance institutions. All interviews were conducted using set of structured interview questions.
3.4.3 Observation
Observation is an eye sight inspection followed by writing or drawing, depending on what the researcher surveys (Adam & Kamuzora, 2008). During data collection, the researcher visited established enterprises to obtain first-hand information to be related to information collected through interviews and questionnaires.
3.5 Validity and Reliability
Kothari (2004) indicates that sound measurement must meet the test of validity, reliability and practicality. According to Kothari, validity refers to the extent to which a test measures what one actually wishes to measure. The questionnair interview and observations guide were given to research supervisors to check whether the instrument reflects what it sought to measure through content validation measurement. Suggestions and comments made were incorporated in the final document before reliability testing and final administration in the field.

Creswell (2011) defines reliability as the extent to which an item triggers same responses every time it is administered. To ensure reliability test was met, a pilot study was conducted in some of the SMEs in Uasin Gishu County. The questionnaires were pretested two times in each sub county by involving 10 respondents since the number required for pre-tests should not to be too large. Mugenda and Mugenda (2003) suggest that the pre-test sample should be between 1% and 10% depending on the sample size. Here, the subjects involved in pre testing the research instruments were encouraged to make comments and suggestions concerning the instructions, clarity of questions and relevance. A reliability test was carried out to establish whether the questionnaires met the desired outcome. The parts that were tested for reliability were section B to E of the questionnaire. The Cronbach’s Alpha reliability co-efficient was used in computing the reliability value with the help of SPSS. A reliability co-efficient of 0.60 was set as a cut-off point as proposed by Fraenkel and Wallen (2000). The results of the study showed that the reliability values for the five variables were 0.726. Based on Fraenkel and Wallen (2000), the instruments were deemed reliable.

3.5 Description of Data Collection Procedure
After ensuring that the research instruments were reliable and valid for data collection, the research instruments were prepared for fieldwork. First, research authorization letter was sought from Catholic University of Eastern Africa (CUEA) to facilitate data collection from Uasin Gishu County. The authorization letters served as means of undertaking research in SMEs and micro-finance institution in County. Upon acquisition of written permission, entrepreneurs were sampled and open and closed ended questionnaires to fill. This was done after obtaining consent from them to act as respondents in the study. The questionnaires were interpreted where necessary. The process of data collection took four weeks. For interview sessions, appointments were made with the selected SMEs within the county.

3.6 Description of Data Analysis Procedure

Data analysis involves the process of arranging the data for processing and analysing so that inferences can be made resulting in formulation of theories (Saravanavel, 1992). After the collection of data from the field, the data was edited, coded, categorised and tabulated. Editing of data was made to detect errors and omissions and to make sure that the data was prepared for tabulation. Descriptive statistics including means, percentages and standard deviations was used to enable the researcher to come up with clear counts concerning the responses.

For inferential statistics, a correlation analysis was conducted to test the relationship micro finance credit and performance of SMEs Uasin Gishu County. In this case, Pearson Product Moment Correlation Coefficient was used to test the relationship between low interest rates, favorable grace periods, favorable initial ceiling amounts and achievable collaterals and incease employment, increase profit, increase outlet, increase capital. Moreover, multiple regression analysis was used to test the hypothesis for the study in order to determine the overall effect of micro finance credit on the performance of small and medium enterprises.

CHAPTER FOUR 4.0 PRESENTATION DISCUSSION AND INTERPRETATION OF FINDINGS
This chapter presents the results of the data analysis, interpretation of findings and discusses the effects of micro finance credit on the performance of SMEs in UG a total of 100enterpreneures participated in the study. The presentation of research findings was guided by the following research questions: (i) What are the effects of MFIs credit on the growth of SMEs capital? (ii) How does MFIs credit effect growth of SMEs human resource? (iii) To what extend does MFIs credit improve financial assistance towards SME growth? (iv) Why is micro finance credit not popular in the county?
4.1 Presentation of Findings
4.1.1 Demographic Data of Respondents
The entrepreneurs were asked to indicate their gender, age bracket, educational background and work experience on the questionnaire. The results are given in Table 4.1 below;

Variable | Category | Frequency | Percent | Gender | Male | 62 | 62 | | Female | 38 | 38 | | Total | 100 | 100.0 | Age bracket | 20 yrs and below | 4 | 4 | | 21 - 30 yrs | 25 | 25 | | 31 - 40 yrs | 43 | 43 | | 40 yrs and above | 28 | 28 | | Total | 100 | 100.0 | Educational background | Primary | 8 | 8 | | Secondary | 72 | 72 | | Collage | 20 | 20 | | Total | 100 | 100.0 | Experience in business | 0 - 5 yrs | 18 | 18 | | 6 - 10 yrs | 34 | 34 | | 11 - 15 yrs | 36 | 36 | | Over 15 yrs | 12 | 12 | | Total | 100 | 100.0 |

Results showed that 62(62%) of the enterpreneurs were male while 38 (38%) were female. The low number of female enterpreneurs is attributed to the attitude of the locals towards access to credit.Findings also showed that enterepreneurs 43(43%) were aged between 31-40 years, 25 (25%) were 21-30 years, 28 (28%) were 40 years and above while only 4 (4%) reported to be 20 years and below. This implies that all categories of enterpreneurs were involved in answering the study research questions. Results on education status revealed that 20 (20%) went upto collage level, 72 (72%) went to secondary school while 8(8%) only attende primary. Regarding their experience in business 18(18%) have less than 5 years, 34(34%) have 6-10 years, 36(36%) have 11-15 years 12(12%) have 15 and above years. This experience is important in determining the extent to which enrepreneurs have knowledge in micro credit.

4.1.2 Influence of MFIs Interest Rates on borrowing
Interest rate was the dependent variable in the study. Entepreneurs were asked to give their responses on their influence of interest rates on loan borrowing by agreeing (5) or disagreeing (1) with the statements provided to them in the questionnaire. The descriptive analysis results are given in Table
Table 4.2 Influence of interest rates on borrowing Influence | N | Mean | Std. Deviation | As an entepreneur I take loans influenced by interest rates. | 100 | 4.4545 | .63751 | I strongly believe in interest rates on loans. | 100 | 4.3766 | .60583 | I have a strong desire to take loan with least interest rate | 100 | 4.1883 | .92014 | Valid N (Listwise) | 100 | 4.3398 | 0.72116 |

Results showed that most entepreneurs are influenced by interest rates (M=4.33 and SD=0.72). Among the three statements measured, entepreneurs showed willingness to take loans with minimum interst rates (M=4.45 and SD=0.63). Secondly, they agreed (M=4.37 and SD=0.61) that they strongly believed in interest rates on loans. Lastly, they indicated (M=4.19 and SD=0.92) that they had a strong desire to take loans with least interest loans. 4.1.3 Provision of Microfinance Services The respondents were asked an open ended question whereby they were asked to state the services they receive from MFIs. The respondents stated the services listed in table below.
Table 4.3: Distribution of Services Offered by MFIs Services Offered | Frequency | Percent | Loans | 100 | 100 | Savings facilities | 100 | 100 | Training | 50 | 50 | Micro Insurance | 10 | 10 | Payment facilities | 4 | 4 |

4.1.4 Distribution of respondents in respect to source of initial capital for their
Business

The respondents were required to indicate what was their major source for financing their business at the start-up point? The results are presented in table below.
Table 4.4: Distribution of respondents in respect to sources of their initial capital Sources of initial capital | Frequency | Percent | Personal savings, friends and family | 11 | 11 | Loans from MFIs | 43 | 43 | Loans from banks | 31 | 31 | Other sources | 15 | 15 | | | | Total | 100 | 100.0 |

According to the findings, 11 respondents indicated that their initial capital was their own savings with assistance from friends and family members. This translated to 11% .31(31%) of the respondents indicated that their major source was through loans from MFIs. 43(43%) respondents said they obtained their initial capital from commercial banks whereas 15(15%) respondents indicated their initial capital was from other sources.

4.1.5 Distribution of respondents in respect to source of subsequent capital for their business.

Table 4.4: Distribution of financing additional capital requirements Sources of finance | Frequency | Percentage | Retained earnings | 35 | 35 | Loans only | 40 | 40 | Retained Earnings and Loans | 25 | 25 | | | | | | | Total | 100 | 100.0 |

In terms of financing additional capital, 35 respondents said it was through retained earnings, 40 showed through getting further loans only and 25 said it was through both loans and retained earnings. This translated to 35% finding through borrowing alone, 40% through retained earnings and 25% through both retained earnings and borrowing. These results suggests that most SMEs are able to effectively and efficiently allocate the initial borrowed loans and thus with knowledge gained through training by MFIs, they are able to register positive results and also make savings. The low percentage of using loans only shows that business financial performance is sound thus SMEs are able to plough back profits to expand their business.
The study through this question intended to find out if MFIs offer similar services and from the findings, all the100 respondents indicated that they got three main services namely the loans, saving facilities and training. Only 10 respondents indicated that they use micro insurance and 4 respondents said they use payment facilities provided by the micro finance institutions. This translated to 21.84% and 8.05% respectively.
These findings suggest that most of the MFIs are offering credit accompanied by training in business skills and other relevant knowledge that enables young entrepreneurs to respond to business challenges. Also savings is equally being encouraged by MFIs through offering savings accounts especially amongst the deposit taking MFIS.

4.1.6 Distribution of respondents in respect to source of initial capital for their business
The respondents were required to indicate what was their major source of financing their business at the beginning? The results are presented in table below.
Pie chart 4.1: Whether the Enterprises benefit from Loans from Microfinance Institutions

Majority (61%) of the respondents indicated that their business enterprises benefit from loans from microfinance institutions, while only 39% of the respondents indicated otherwise.
The study sought to establish the reasons as to why the enterprises obtained loans from MFI„s that made them to seek financial assistance from the MFIs.

4.1.7 Why Enterprises obtain loans from MFIs
Table: Reasons as to why the enterprises obtained loans from MFI’s Reasons | Frequency | Percentage | Easy loan repayment | 30 | 30 | Amount offered | 27 | 27 | Interest rate | 43 | 43 | | | | | | | Total | 100 | 100.0 |

From the study, majority (43%) of the respondents indicated that their enterprises resorted to seeking financial assistance from the MFIs due to interest rate, 30% of the respondents indicated easy loan repayment, while 27% of them indicated that the amount offered triggered their enterprises to seek financial assistance from the MFIs.
On others of the respondents indicated that business expansion and the need to increase production volume forced their enterprises to look for the financier. Other respondents indicated that their business enterprises sought for more than one financier to cover production cost, to improve on the performance of the business and to increase capital of the business.
The respondents were required to indicate the loan repayment period as per the conditions of MFI.

4.1.8 Time Allowed by MFIs for Repayments

Table4.6: Length of Time Allowed Repaying the MFI Loans Loan Repayment Period | Frequency | Percent | 6 months-1 year | 55 | 55 | Above 1 year | 39 | 39 | Above 5 years | 6 | 6 | | | | | | | Total | 100 | 100.0 |

Majority of the respondents, shown by 55%, reiterated that the loan repayment period as per the conditions of the MFIs was below 1year, 39% of them indicated over 1 year, while 6% of the respondents indicated that their enterprises were required to repay their loans in the period over 5yearsThe respondents were required to indicate their opinion on the rate of the loan services offered by the MFIs.

4.1.9Rating MFIs Table 4.7: The rate of the loan services offered by the MFI’s Frequency of compensation | Frequency | Percent | Excellent | 39 | 39 | Good | 54 | 54 | Fair | 6 | 6 | No idea | 1 | 1 | Total | 100 | 100.0 |

From the study, 54.5% of the respondents indicated that the loan services offered by the MFIs were good, 39.4% rated the loan services offered by the MFIs as being excellent, while 6% of them rated the loan services offered by the MFIs as being fair as 1% had no idea.
The respondents were further required to indicate whether they face any challenges as a loan beneficiary from the MFIs.
4.3 Interpretation of Findings
4.3.1 Multiple Regression Analysis
In addition, the researcher conducted a multiple regression analysis so as to determine the effect of microfinance credit on performance of SMEs in Uasin Gishu County, Kenya. Multiple regression is a statistical technique that allows us to predict a score of one variable on the basis of their scores on several other variables. The main purpose of multiple regression is to learn more about the relationship between several independent or predictor variables and a dependent or criterion variable.
The coefficient of determination is a measure of how well a statistical model is likely to predict future outcomes. The coefficient of determination, r2 is the square of the sample correlation coefficient between outcomes and predicted values. As such it explains the extent to which changes in the dependent variable can be explained by the change in the independent variables or the percentage of variation in the dependent variable (Financial sustainability of SMEs) that is explained by all the three independent variables (savings, credit and entrepreneurship development).
4.3.2 Regression Analysis
In order to establish the relationship between independent and dependent variables, a multiple regression was conducted. The research study aimed at evaluating the relationship between microfinance credit and performance of SMEs in Uasin Gishu County.
The study also revealed that 87.3% of performance in the SMEs could be explained by the variables under study. From this study it is evident that at 95% confidence level, the variables produce statistically significant values and can be relied on to explain performance in the SMEs sector in Kenya. Table4.8: Model Summary

Model | R | R Square | Adjusted R Square | Std. Error of the Estimate | 1 | .934a | .873 | .802 | .312 | a. Predictors: (Constant), Microfinance credit, Outstanding debts, Sales turnover, Size of loan |

From the analysis, the independent variable microfinance credit in this study contributed to 98.3% of the variation in performance of SME‟s in Uasin Gishu County of SME‟s as explained by adjusted R2 of 87.3. The study conducted an Analysis of Variance, in order to test the significance of the model. The findings were as shown below:
4.3.3 Analysis of Variance
Analysis of variance shows the relationship between the two variables. This section shows you the p-value (“sig” for “significance”) of the predictor‟s effect on the criterion variable. P-values less than .05 are generally considered “statistically significant. In this case the researcher will observe the relationship between liquidity and financial performance.
Table 4.9: ANOVA Model | Sum of Squares | df | Mean Square | F | Sig. | 1 | Regression | 2.107 | 4 | .5268 | 5.2314 | .000a | | Residual | 3.122 | 31 | .1007 | | | | Total | 5.229 | 35 | | | | a. Predictors: (Constant), low interest rates b. Dependent variable, rate of equity |

From the ANOVAs results, the probability value of 0.000 was obtained implying that the regression model was statically significant in predicting the relationship between microfinance credit and performance of SME‟s in Uasin Gishu County and the predictor variables as it was less than α=0.05. By the help of the F-Test table (5%, 4) tabulated value was 3.472 which was less than F= 5.2314 as well indicated that the model was significant.

Table 4.10 Coefficientsa Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | | B | Std. Error | Beta | | | 1 | (Constant) | 1.215 | 1.013 | .002 | 3.145 | .000 | | Microfinance credit | .001 | .335 | .102 | 1.101 | .005 | | Outstanding debt | .224 | .103 | .128 | .725 | .002 | | Sales turnover | .302 | .657 | .123 | .345 | .004 | | Size of the loan | -.201 | .768 | .001 | .789 | .002 | a. Dependent Variable: R.O.A |

The researcher conducted a simple regression analysis so as to determine the relationship between performance of SMEs in Uasin Gishu County (dependent variable) and microfinance credit of SMEs in Uasin Gishu County. The following regression equation was obtained:
ROA = 1.215+.001X1+.224X2+.302X3+.201X4
From the regression model obtained above, holding all the other factors constant, performance of SMEs in Uasin Gishu County .The obtained regression equation further implied that there was a direct relationship between microfinance credit and performance of SMEs in Uasin Gishu County of SMEs. The analysis was undertaken at 5% significance level. The criteria for comparing whether the predictor variables were significant in the model was through comparing the corresponding probability value obtained and α=0.05. If the probability value is less than α, then the predictor variable is significant. Therefore, from the above analysis microfinance credit was significant in the model as its corresponding predictor variables were less than 5%.

CHAPTER FIVE
SUMMARY, CONCLUSIONS AND RECOMMENDATIONS
This chapter presents a summary of research findings, conclusions, recommendations and suggestions for further studies on the effects of microfinance credit on the performance of small and medium entreprises in Uasin Gishu County, Kenya.
5.1 Summary
The study investigated how effective is micro finance credit on the performance of SMEs in UG County. Data was collected by use of questionnaires, interview and observation guide. 100 entepreneurs participated in anering research questions.
5.1.1 Demografic data
The demographic data results showed that most entepreneurs had done business for a period of 11-15 years. Most of them had studied upto secondary level.
5.1.2 Loan payment period
Result showed that 55% paid between 6months to 1 year, 39% paid for more than 1 year while 6% paid back in more than 5 years.
5.1.3 Provisions of MFI services
Study showed that 100% new MFIs for the provision of loans, another 100% for saving services, 50% identified their training services, 10% had knowledge of their insurance services while 4% for their paryment services.
5.1.4 Sources of their initial capital
11% indicated that its from friends, family and personal savings, 43 borrowed loans from MFIs while 31 borrowed from banks and 15% got from other sources.
5.1.5 Subsequent capital for business
Study showed that 35% got from retained earnings, 40% from loans only while 25% got fom both retained earnings and loans. 5.1.6 Reasons for obtaining loans from MFIs
30% recorded easy payment as a reason for obtaining loans from MFIs, 27% indicated amount offered as a reason and 43% cited interest rates as the reason.
5.1.7 Time allowed for loan repayment
Study found that 55% were given within 6months to 1 year to repay their loans, 39% given above 1 year and 6% above one year.
5.1.8 Benefits of using MFCs
Data results showed that 61% of entepreneurs had befits using MFC while 39% indicated no benefits.
5.1.9 Rating of MFIs
Data results indicated that 39% rated MFIs services as excellent, 54% rate the services as good, 6% rated them as fair while 1% had no idea.

5.2 Conclusions
MFIs are concerned with provision of financial services to people who are economically poor and who therefore experience financial exclusion in that they do not have ready access to mainstream, commercial financial services. It is concerned with provision of financial services to poor people using means which are just, fair and sustainable for example they accept social collateral rather than financial collateral, access to larger amounts of loan if repayment is performance is positive, easy way to access finance in not much paper work, and easy and short procedures.
A large number of Uasin Gishu residents derive their livelihood from the SMEs. However in spite of the importance of this sector, experience shows that provision and delivery of credit services to the sector by formal financial institutions such as commercial banks and MFIs has been below expectation. This means that it is difficult for the poor to move out of poverty due to lack of finance for their productive activities. Small-scale loans can relieve capital constraints that might otherwise preclude cash-strapped entrepreneurs from investing in profitable businesses, while savings services can create opportunities to accumulate wealth in safe repositories and to manage risk through asset diversification.
As SMEs grow they require funds to finance growth in fixed asset and increase working capital. SMEs therefore require long-term credit in ever increasing amounts.
SMEs needs funds so that they can purchase raw materials supplies and carry out activities that they need to facilitate the production process.
The study found that all SMEs borrow investment capital and they use it for the purpose in which they borrowed for, most of them do not have other source of financing other than from micro-finance institutions and they did not have other form of financing before they started receiving financing from microfinance institutions.
The study finally concludes that ROA increased with each consecutive loan showing that microfinance services enhance performance of SMEs in Uasin Gishu County.
The regression results imply that microfinance credit contribute more to the financial performance of SMEs and hence higher return on assets.

5.3 Recommendations
Based on the findings of the study, the following recommendations are made: i). There is need to provide an enabling environment for SME‟s to grow and thrive, therefore there is a need to develop strategies to enhance increased access to microfinance credit by SME‟s from commercial banks and microfinance institutions. ii). It is important for the government to set up policies that will ease microfinance credit to SME‟s. These policies should be in line with both the owners of SME‟s and financial institutions in order to prevent putting hindrances to potential and credit worthy customers who seek to expand or start up a business. This will create a window for growth and development of the economy as a result of more job opportunities and increased flow of money circulation in the economy. iii). Financial institutions should ensure that they sensitize the owners of SMEs on best financial management practices. This will help the owners of SME‟s to account for loans borrowed. Lending institutions should also advise borrowers on how to appraise their projects for viability to ensure that they make wise decisions when investing in projects. iv). The study recommends that MFIs partner with the county governments and other stakeholders so as to create awareness of the availability and the process of accessing microfinance loans. Since MFIs have poverty alleviation as its vision they should consider lending startup capital so that the welfare of the business and the borrower can be monitored. v). The study recommends the central bank should set policies and procedures to prevent barriers that inhibit potential owners and managers of SME‟s from accessing credit facilities. This will create conducive environment for SME‟s to growth and expand. It will also open up opportunities for jobs and this will enhance economic growth. vi). Financial institutions should also provide financial advisory services to individual proprietors when advancing credit to them; lower lending rates while improving service delivery and train people on risk management and financial management. The Government should also regulate financial institutions to ensure that the owners and managers of SME‟s get access to information in order to make the right investment decisions.

5.4 Suggestions for Further Study
This study focused on SMEs in Uasin Gishu County and therefore the findings of this study cannot be generalized to all the SMEs in the 47 counties in Kenya. The study recommends that further research could be conducted on SMEs countrywide to investigate on the effects of microfinance credit on performance of SMEs to find out whether there are commonalities or unique factors. The concentrated on the SMEs, it is important to carry out similar study among large enterprises in order to find out the effect of credit on performance of these firms. Future research should also focus on the different aspects of micro financing on the performance of SMEs. For the small and micro enterprises sector to grow small businesses need to link with the rest of the economy. Most of these businesses are so small that creating a link seems almost impossible. Further research should be done in this area to establish the best way of linking small and micro businesses with large companies in the economy.

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APPENDICES
Appendix I: Research Introductory Letter

Dear respondent,

My name is Dennis Kibet , a student at Catholic University of Eastern Africa, pursuing a Master of Business Administration degree. I am undertaking a research study on “Effects of micro-finance credit on the performance of small and medium enterprises in Uasin Gishu County, Kenya.” In partial fulfilment of the requirements for this degree. You have been selected to participate in this study and the researcher is kindly requesting you to assist in providing the required information to the best of your knowledge by responding to the questionnaire attached.
The information is strictly for academic purposes and personal information will be treated with utmost confidentiality. Your kind assistance will be highly appreciated.

Yours faithfully,

Dennis Kibet K.
BCOM student

APPENDIX II: QUESTIONNAIRE
Background – Personal Information
1. Name................................................. Optional
2. What is your Gender? [ ] Male [ ] Female
3. What is your age? Below 20 years [ ] Between 21-30 [ ] Between 31-40 [ ] Above 40 years [ ]
4. What is your highest level of education? Primary school [ ] Secondary school [ ] College [ ]
5. How long have your business been operational?
Duration Option Less than 5 year [ ] 6-10 years [ ]
11-15 years [ ]
Over 15 years [ ]

Part II Provision of Microfinance Services
6. Tell us about other valuable services you get from MFIs
......................................................................................................
......................................................................................................
......................................................................................................
7. What was the major source of your start-up capital?
A Personal Savings & Friends and relatives [ ]
B Loans from banks [ ]
C Other sources [ ]
D Others sources [ ]
If other sources please state which source?
..................................................................................................
..................................................................................................
..................................................................................................
8. What was the major source of financing additional capital?
A Retained profits [ ]
B Loans and retained earnings [ ]
C Loans only [ ]
9. Do you benefit from loans from microfinance institutions? Yes [ ] No [ ]
If Yes, how
......................................................................................................

10. Do Interest rates influence borrowing?
……………………………………………………………
……………………………………………………………..
……………………………………………………………..

11. If you obtain loan from MFIs what made you to seek financial assistance from the MFIs
a. Easy loan repayment [ ]
b. Amount offered [ ]
c. Interest rate [ ]
Others state..........................................
12. What is the loan repayment period as per the conditions of MFI?
a. 6 months-1 year [ ]
b. - 5 years [ ]
c. Above 5 years [ ]
12. In a scale of 1-5, rate the below in respect to training if any by MFIs. Note
1 =No idea; [ ]
2=Fair; [ ]
3= Good; [ ]
4=Excellent [ ]